Floating-point computations dominate the landscape of all AI/ML compute but also in automotive, avionics and healthcare. While performance and compute errors dominated the landscape of floating-point ...
Essentially all AI training is done with 32-bit floating point. But doing AI inference with 32-bit floating point is expensive, power-hungry and slow. And quantizing models for 8-bit-integer, which is ...
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